Senior CV/ML Engineer

End-to-End Computer Vision Systems

The Opportunity

We are building a Computer Vision platform that automates the full CV model lifecycle, from data preparation and model training through evaluation, deployment, and monitoring.

You will join a small, autonomous team of 3 to 5 engineers (plus interns) working alongside AI/ML engineers and computer vision scientists at ST Engineering.

You are the subject matter expert for Computer Vision across the entire lifecycle: data preparation, model training, evaluation, deployment, monitoring, and automation. You will also build CV proof-of-concepts to validate product ideas before we commit to building at scale.

Scope: 2D image and video. This role does not cover 3D vision, point clouds, LiDAR, or sensor fusion.

What You'll Build

Computer Vision Models and Pipelines (Primary Focus)

Train, fine-tune, and evaluate CV models for classification, detection, and segmentation on real, imperfect data
Own the data side: dataset curation, labeling strategy and quality control, augmentation pipelines, and dataset versioning
Define evaluation methodology that reflects the use case (mAP, IoU, precision and recall at the operating point), run error analysis, and build regression tests that stop weak models from shipping
Package and deploy models to production (ONNX Runtime, TorchServe, or similar), including inference optimization against latency and throughput targets
Monitor deployed models: performance and data drift, failure case capture, and retraining triggers

Automation Platform

Build backend services (Python, FastAPI) that turn the above into repeatable, automated pipelines the team and the platform can trigger programmatically
Wrap CV toolkits (PyTorch, OpenCV, Ultralytics YOLO) so data prep, training, evaluation, and deployment can be orchestrated end to end
Design clean, versioned, documented APIs that internal teams and platform services consume
Implement orchestration for multi-step pipelines with retry, rollback, and defined SLAs

Proof-of-Concepts

Rapidly prototype end-to-end Computer Vision applications to validate product ideas before committing to a full build
Translate prototype learnings into production architecture decisions

Infrastructure and Quality

Ship production systems with containerization (Docker, Kubernetes), CI/CD (GitHub Actions), and monitoring (Prometheus, Grafana)
Establish engineering quality through testing (pytest), observability, and clean architecture

What You Bring

Must Have

Minimum 4 years building Computer Vision systems, with a mix of end-to-end ownership: you have taken CV models from raw data through training and evaluation into a production deployment that real users or systems depend on, rather than prototypes that stopped at a benchmark
Hands-on model work: you have trained, fine-tuned, and evaluated your own CV models (classification, detection, segmentation), not only built infrastructure around models other people trained
Data preparation depth: labeling and annotation quality, class imbalance, augmentation strategy, and the data-quality failure modes that quietly degrade model performance
Deep PyTorch and OpenCV experience
Strong Python with production-grade API development (FastAPI)
Model packaging and serving in production (ONNX Runtime, TorchServe, or similar)
Deployment and operations: Docker, CI/CD (GitHub Actions), and monitoring of live models
Solid system design and architecture skills

Nice to Have

GPU infrastructure: CUDA and cuDNN management, multi-GPU training on Ubuntu servers
Inference optimization beyond ONNX: TensorRT, OpenVINO, Triton, or edge runtimes
Kubernetes at production scale
Experiment tracking and automated model evaluation (MLflow or Weights & Biases)
Classical CV: geometry and calibration, tracking

What We Offer

Hybrid work setup: about 2 to 3 days in office per week
Startup feel with enterprise resources, in an international team with backgrounds from Lazada, Gojek, and IBM
Low-bureaucracy, high-impact environment where your models and code go into real deployments
Direct collaboration with AI researchers and computer vision scientists
Culture of experimentation, self-development, and knowledge sharing

Senior CV/ML Engineer (2 Years Contract)